CN117574177B - Data processing method, device, medium and equipment for user wire expansion - Google Patents
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Abstract
The invention relates to the field of data processing, in particular to a data processing method, a device, a medium and equipment for user wire expansion, which comprise the following steps: according to the user list corresponding to each target IP, a first association degree and a first association degree set between any two target IPs are obtained, according to the IP list corresponding to each target user and the first association degree set, a second association degree and a second association degree set between any two target users are obtained, according to the second association degree set and an association degree threshold value, an association user list corresponding to each target user is obtained, the association relation between the target IPs is represented by analyzing the association degree between the user lists corresponding to the target IPs, the connection relation between the target IPs and the target users and the influence of the association relation between the target IPs on the association relation between the target users are further comprehensively considered, the accuracy of the second association degree is improved, and the accuracy of user line expansion is further improved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a data processing method, apparatus, medium and device for user wire expansion.
Background
With the popularization of intelligent devices and the rapid development of networks, the daily life of users is closely related to the intelligent devices and networks, so that when the users expand lines, the association relationship among the users can be represented by the intelligent devices of the users and the connected network information, and the judgment and screening of the association users are completed.
The current user line expansion method mainly carries out similarity analysis according to the age, sex, application program downloading information, usage information and other self attributes of the user, namely, determines whether the unknown user belongs to a specific user group or not by carrying out similarity calculation on the self attribute of the unknown user and the self attribute of the known user so as to finish user line expansion based on the known user.
However, in the method, a large amount of attribute data of known users need to be acquired in advance, so that the cost of user line expansion is high, the association relationship between users is complex and various along with popularization of intelligent equipment and wide application of a network, the change degree of the attribute information of the users along with the change of the intelligent equipment and the network is low, the matching between the associated users is difficult to accurately perform, and the accuracy of user line expansion is low.
Therefore, how to improve the accuracy of the subscriber line extension is a urgent problem to be solved.
Disclosure of Invention
Aiming at the technical problems, the technical scheme adopted by the invention is a data processing method for user wire expansion, which comprises the following steps:
Acquiring a user list corresponding to each target IP and an IP list corresponding to each target user, wherein the user list comprises IDs of a plurality of target users, and the IP list comprises a plurality of target IPs;
According to the user list corresponding to each target IP, a first association degree between any two target IPs is obtained, and then a first association degree set is obtained;
Acquiring a second association degree between any two target users according to the IP list and the first association degree set corresponding to each target user, and further acquiring the second association degree set;
And acquiring a corresponding associated user list of each target user according to the second association degree set and a preset association degree threshold.
The invention also provides a data processing device for user wire expansion, which comprises:
The data acquisition module is used for acquiring a user list corresponding to each target IP and an IP list corresponding to each target user, wherein the user list comprises IDs of a plurality of target users, and the IP list comprises a plurality of target IPs;
the first association degree acquisition module is used for acquiring a first association degree between any two target IPs according to the user list corresponding to each target IP, and further acquiring a first association degree set;
the second association degree acquisition module is used for acquiring a second association degree between any two target users according to the IP list corresponding to each target user and the first association degree set, and further acquiring the second association degree set;
and the associated user acquisition module is used for acquiring an associated user list corresponding to each target user according to the second associated degree set and a preset associated degree threshold value.
The present invention also provides a non-transitory computer readable storage medium storing at least one instruction or at least one program, where the at least one instruction or the at least one program is loaded and executed by a processor to implement the above-mentioned data processing method for user extension.
The invention also provides an electronic device comprising a processor and the non-transitory computer readable storage medium described above.
The invention has at least the following beneficial effects: the user list corresponding to each target IP and the IP list corresponding to each target user are obtained, so that a data basis is provided for representing the association relationship between the target users and further expanding the line of the users; according to the user list corresponding to each target IP, a first association degree between any two target IPs is obtained, a first association degree set is obtained, the association degree between the corresponding two target IPs is represented by analyzing the similarity of the user lists corresponding to the two target IPs, and the representation accuracy of the association relation between the IPs is improved; according to the IP list corresponding to each target user and the first association degree set, the second association degree between any two target users is obtained, the second association degree set is obtained, the association user list corresponding to each target user is obtained according to the second association degree set and a preset association degree threshold value, the connection relation between the target IP and the target users and the influence of the association relation between the target IP on the association relation between the target users are further comprehensively considered, the accuracy of the obtained second association degree is improved, and the accuracy of user line expansion is further improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a data processing method for user line expansion according to an embodiment of the present invention;
FIG. 2 is a flowchart of a data processing method for user line expansion according to another embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a data processing apparatus for user line extension according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a data processing apparatus for user line extension according to another embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
The first embodiment provides a data processing method for user line expansion, which includes the following steps, as shown in fig. 1:
S100, a user list corresponding to each target IP and an IP list corresponding to each target user are obtained, wherein the user list comprises IDs of a plurality of target users, and the IP list comprises a plurality of target IPs.
The user list is a list corresponding to a target user connected with the target IP in a preset time period, and comprises the ID of the target user and the unique identity of the target user. The IP list refers to a list of IPs to which the target user is connected for a preset period of time. The preset time period may be set by the practitioner according to the actual situation, for example, the preset time period may be a time period of one month, three months, six months, one year, or the like.
The user list corresponding to the target IP and the IP list of the target user can represent the corresponding connection relation between the target user and the target IP, and the association relation between the target users can be further represented by carrying out correlation analysis on the user list and the IP list, so that the associated user of each target user is determined, and the task of expanding the line of the users is completed.
The user list corresponding to each target IP and the IP list corresponding to each target user are obtained, and a data basis is provided for representing the association relationship between the target users and further expanding the line of the users.
In a specific embodiment, in order to improve the wire-expanding quality of the target user, the target user is screened from the preset users, and the target IP is screened from the preset IPs.
It can be understood that the connection relationship between the preset user and the preset IP is complex and various, and there may be times of connecting the IP, abnormal users appearing at the time point of connecting the IP, and abnormal IPs appearing at the location of the geographic area to which the user belongs, the number of connected users, and the number of wifi allocated, which results in lower accuracy of the user line expansion result.
Therefore, the embodiment obtains the total number of connections between each preset user and the preset IP in the preset time period and the connection time point of each connection preset IP, and when the total number of connections is greater than the preset number threshold and the connection time point is within the preset time point range, determines the corresponding preset user as the target user, so as to screen out the times of connection IP and the abnormal users in the time point of connection IP, and improve the quality of the target user.
The preset quantity threshold and the preset time point range can be set by an implementer according to actual conditions. For example, the preset number threshold may refer to the average of the total number of connections between all preset users and all preset IPs; the time point range comprises an upper time point limit and a lower time point limit, specifically, in a set of connection time points between all preset users and all preset IPs, the occurrence frequency corresponding to each connection time point is obtained, the average value of the occurrence frequencies corresponding to all connection time points is calculated, then the minimum connection time point with the corresponding occurrence frequency larger than the average value of the occurrence frequencies is determined as the lower time point limit, and the maximum connection time point with the corresponding occurrence frequency larger than the average value of the occurrence frequencies is determined as the upper time point limit, so that the preset users are screened to improve the quality of the target users.
Meanwhile, the embodiment obtains geohash values corresponding to the geographic area position to which each preset IP belongs in a preset time period, the total number of users connected and the total wifi number of the wifi allocated, when the geohash values are smaller than a preset geohash threshold, the total number of users is smaller than a preset user number threshold, and the total wifi number is smaller than the preset wifi number threshold, the corresponding preset IP is determined to be the target IP, so that the abnormal IP appears in the geographic area position to which each preset IP belongs, the number of connected users and the wifi allocated is screened out, and the quality of the target IP is improved.
The preset geohash threshold, the preset user quantity threshold and the preset wifi quantity threshold can be set by an implementer according to actual conditions.
The target users are obtained by screening from the preset users, and the target IP is obtained by screening from the preset IP, so that the quality of the target users and the quality of the target IP are improved, and the wire expansion quality of the target users is further improved.
S200, according to the user list corresponding to each target IP, acquiring a first association degree between any two target IPs, and further acquiring a first association degree set.
If the similarity of the user lists corresponding to the two target IPs is higher, the higher the association degree between the two target IPs is represented, so that the first association degree between any two target IPs is obtained according to the user list corresponding to each target IP, and then a first association degree set is obtained.
In a specific embodiment, the step of obtaining the first association degree between any two target IPs according to the user list corresponding to each target IP further includes the following steps:
Acquiring a user intersection and a user union between any two target IPs according to a user list corresponding to each target IP;
acquiring a first user quantity according to the user intersection;
acquiring a second user quantity according to the user union;
and determining the ratio of the first user quantity to the second user quantity as a first association degree between any two target IPs.
In one embodiment, the user list may include IDs of target users, where the user intersection includes IDs of a plurality of target users, specifically, when the corresponding target user IDs in the user lists of any two target IPs are identical, the target user IDs corresponding to any two target IPs are determined to be the target user IDs in the user intersection, so that a user intersection between any two target IPs is obtained, and a user union between any two target IPs is obtained.
In another embodiment, the user list may further include an ID and a connection time of the target user, where the connection time refers to a time when the device corresponding to the target user connects to the corresponding target IP, and the user intersection includes a plurality of IDs of the target users, specifically, when the corresponding target user IDs and connection times in the user lists of any two target IPs are both consistent, the target user ID corresponding to the any two target IPs is determined to be the target user ID in the user intersection, so that a user intersection between any two target IPs is obtained, and a user union between any two target IPs is obtained.
The higher the ratio of the first user number corresponding to the user intersection in the second user number corresponding to the user union, the higher the similarity of the corresponding two user lists is, and the higher the association degree between the corresponding two target IPs is further characterized, so that the ratio of the first user number to the second user number is determined as the first association degree between any two corresponding target IPs.
By analyzing the similarity of the user lists corresponding to the two target IPs, the association degree between the two corresponding target IPs is represented, and the accuracy of representing the association relationship between the IPs is improved.
S300, obtaining a second association degree between any two target users according to the IP list and the first association degree set corresponding to each target user, and further obtaining the second association degree set.
And combining the first association degree between the target IPs with the IP list corresponding to each target user to acquire a second association degree between any two target users, wherein the second association degree is used as a basis for expanding the line of the users.
In a specific embodiment, the step of obtaining the second association degree between any two target users according to the IP list and the first association degree set corresponding to each target user further includes the following steps:
Acquiring an IP intersection and an IP union between any two target users according to the IP list corresponding to each target user;
acquiring a first weight corresponding to each target IP in the IP intersection according to the first association degree set;
acquiring the number of the IPs according to the IP union;
and calculating the sum of first weights corresponding to all the target IPs in the IP intersection, and determining the ratio of the sum of the first weights to the number of the IPs as a second association degree between any two target users.
The IP intersection and the IP union comprise a plurality of target IPs, a first weight corresponding to each target IP in the IP intersection is obtained according to a first association degree between the target IPs in the IP intersection, the association degree between any two corresponding target users is further represented by combining the IP union, a second association degree is obtained according to the association degree, the second association degree is used as a basis for expanding lines of the users, and the line expansion accuracy of the target users is improved.
The first association degree and the IP union between the target IPs in the IP intersection are combined to obtain the second association degree between any two corresponding target users, the connection relationship between the target IPs and the target users and the influence of the association relationship between the target IPs on the association relationship between the target users are further comprehensively considered, and the accuracy of the obtained second association degree is improved, so that the line expansion accuracy of the target users is improved.
In a specific embodiment, the step of obtaining the first weight corresponding to each target IP in the IP intersection according to the first association degree set further includes the following steps:
Taking any target IP in the IP intersection as an IP to be processed, and taking other target IPs except the IP to be processed in the IP intersection as candidate IPs;
According to the first association degree set, a first association degree between the to-be-processed IP and any candidate IP is obtained, and the average value of the first association degrees between the to-be-processed IP and all candidate IPs is calculated;
determining the average value of the first association degree as a first weight corresponding to the IP to be processed;
Traversing each target IP in the IP intersection to obtain a first weight corresponding to each target IP in the IP intersection.
And determining the average value of the first association degrees between the to-be-processed IP and all the candidate IPs as the first weight corresponding to the to-be-processed IP, and representing the association relationship between the target users by combining the association relationship between the target IPs and the connection relationship between the target users and the target IPs, thereby improving the accuracy of the second association degree and further improving the line expansion accuracy of the target users.
S400, acquiring a corresponding associated user list of each target user according to the second associated degree set and a preset associated degree threshold.
The second association degree between the target users is larger, and the association relation between the two corresponding target users is more compact, so that when the second association degree is larger than a preset association degree threshold, the two corresponding target users are determined to be associated users, an associated user list corresponding to each target user can be further acquired, and the wire expansion task of the users is completed.
The preset association degree threshold value can be set by an implementer according to actual conditions.
In a specific embodiment, the method further comprises the following steps, as shown in fig. 2:
S500, updating the first association degree according to the user list and the second association degree set corresponding to each target IP, acquiring a third association degree between any two target IPs, and further acquiring the third association degree set;
S600, updating the second association degree according to the IP list corresponding to each target user and the third association degree set, acquiring a fourth association degree between any two target users, and further acquiring the fourth association degree set;
s700, according to the fourth association degree set and a preset association degree threshold value, an updated association user list corresponding to each target user is obtained.
The method comprises the steps of obtaining a first association degree between target users, obtaining a first association degree between the target users, obtaining a second association degree between the target users based on the first association degree between the target IP, and updating the first association degree and obtaining a third association degree between the target IP by further combining the user list corresponding to the target IP and the second association degree between the target users, wherein the first association degree and the second association degree between the target users are mutually influenced, so that the third association degree can more accurately represent the association relation between the target IP than the first association degree.
And then, further combining the IP list corresponding to the target users and the third association degree, updating the second association degree and obtaining a fourth association degree between the target users, so that the fourth association degree can more accurately represent the association relation between the target users than the second association degree, and the updated association user list corresponding to each target user is obtained according to the fourth association degree set and a preset association degree threshold value, and the accuracy of the updated association user list is improved.
In a specific embodiment, the step of updating the first association degree according to the user list and the second association degree set corresponding to each target IP to obtain the third association degree between any two target IPs further includes the following steps:
acquiring a second weight corresponding to each target user in the user intersection according to the second association degree set;
And calculating second weight sum corresponding to all target users in the user interaction, and determining the ratio of the second weight sum to the second user quantity as a third association degree between any two target users.
In a specific embodiment, the step of updating the second association degree according to the IP list and the third association degree set corresponding to each target user to obtain the fourth association degree between any two target users further includes the following steps:
according to the third association degree set, a third weight corresponding to each target IP in the IP intersection is obtained;
And calculating the third weight sum corresponding to all the target IPs in the IP intersection, and determining the ratio of the third weight sum to the IP number as a fourth association degree between any two target users.
The method and the device for the online extension of the Internet protocol have the advantages that the first association degree is updated and the third association degree between the target IPs is obtained by combining the second association degree between the user list corresponding to the target IPs and the target users, the accuracy of representing the association relation between the target IPs is improved, the second association degree is further updated and the fourth association degree between the target users is obtained by combining the IP list corresponding to the target users and the third association degree, and the accuracy of representing the association relation between the target users is improved, so that the accuracy of online extension of the users is improved.
The user list corresponding to each target IP and the IP list corresponding to each target user are obtained, and a data base is provided for representing the association relationship between the target users and further expanding the line of the users; according to the user list corresponding to each target IP, a first association degree between any two target IPs is obtained, a first association degree set is obtained, the association degree between the corresponding two target IPs is represented by analyzing the similarity of the user lists corresponding to the two target IPs, and the representation accuracy of the association relation between the IPs is improved; according to the IP list corresponding to each target user and the first association degree set, the second association degree between any two target users is obtained, the second association degree set is obtained, the association user list corresponding to each target user is obtained according to the second association degree set and a preset association degree threshold value, the connection relation between the target IP and the target users and the influence of the association relation between the target IP on the association relation between the target users are further comprehensively considered, the accuracy of the obtained second association degree is improved, and the accuracy of user line expansion is further improved.
Example two
The second embodiment provides a data processing apparatus for user line extension, where the apparatus includes, as shown in fig. 3:
The data obtaining module 31 is configured to obtain a user list corresponding to each target IP and an IP list corresponding to each target user, where the user list includes IDs of a plurality of target users, and the IP list includes a plurality of target IPs;
A first association degree obtaining module 32, configured to obtain a first association degree between any two target IPs according to the user list corresponding to each target IP, and further obtain a first association degree set;
A second association degree obtaining module 33, configured to obtain a second association degree between any two target users according to the IP list and the first association degree set corresponding to each target user, and further obtain the second association degree set;
And the associated user obtaining module 34 is configured to obtain an associated user list corresponding to each target user according to the second association degree set and a preset association degree threshold.
In an embodiment, the first association degree obtaining module 32 further includes the following sub-modules:
The first intersection acquisition sub-module is used for acquiring a user intersection and a user union between any two target IPs according to the user list corresponding to each target IP;
The first user quantity acquisition sub-module is used for acquiring the first user quantity according to the user intersection;
the second user quantity obtaining sub-module is used for obtaining the second user quantity according to the user union;
and the first association degree acquisition sub-module is used for determining the ratio of the first user number to the second user number as the first association degree between any two target IPs.
In an embodiment, the second association degree obtaining module 33 further includes the following sub-modules:
The second intersection acquisition sub-module is used for acquiring an IP intersection and an IP union between any two target users according to the IP list corresponding to each target user;
The first weight acquisition sub-module is used for acquiring a first weight corresponding to each target IP in the IP intersection according to the first association degree set;
The IP quantity obtaining sub-module is used for obtaining the IP quantity according to the IP union;
The second association degree obtaining sub-module is used for calculating the sum of the first weights corresponding to all the target IPs in the IP intersection, and determining the ratio of the sum of the first weights to the number of the IPs as the second association degree between any two target users.
In an embodiment, the first weight obtaining sub-module further includes the following units:
The IP classification unit is used for taking any target IP in the IP intersection as an IP to be processed and taking other target IPs except the IP to be processed in the IP intersection as candidate IPs;
The first average value calculation unit is used for acquiring a first association degree between the to-be-processed IP and any candidate IP according to the first association degree set, and calculating an average value of the first association degree between the to-be-processed IP and all candidate IPs;
the first weight determining unit is used for determining the average value of the first association degree as a first weight corresponding to the IP to be processed;
The IP traversing unit is used for traversing each target IP in the IP intersection and acquiring a first weight corresponding to each target IP in the IP intersection.
In a specific embodiment, the apparatus further includes the following modules, as shown in fig. 4:
a third association degree obtaining module 35, configured to update the first association degree according to the user list and the second association degree set corresponding to each target IP, obtain a third association degree between any two target IPs, and further obtain a third association degree set;
A fourth association degree obtaining module 36, configured to update the second association degree according to the IP list and the third association degree set corresponding to each target user, obtain a fourth association degree between any two target users, and further obtain a fourth association degree set;
the associated user list updating module 37 is configured to obtain an updated associated user list corresponding to each target user according to the fourth association degree set and a preset association degree threshold.
In an embodiment, the third association degree obtaining module 35 further includes the following sub-modules:
the second weight acquisition sub-module is used for acquiring a second weight corresponding to each target user in the user intersection according to the second association degree set;
and the third association degree acquisition sub-module is used for calculating the sum of second weights corresponding to all target users in the user intersection, and determining the ratio of the sum of the second weights to the number of the second users as the third association degree between any two target users.
In an embodiment, the fourth association degree obtaining module 36 further includes the following sub-modules:
The third weight acquisition sub-module is used for acquiring a third weight corresponding to each target IP in the IP intersection according to the third association degree set;
and the fourth association degree acquisition sub-module is used for calculating the sum of third weights corresponding to all the target IPs in the IP intersection, and determining the ratio of the sum of the third weights to the number of the IPs as the fourth association degree between any two target users.
It should be noted that, because the content of information interaction and execution process between the modules and the embodiment of the method of the present invention are based on the same concept, specific functions and technical effects thereof may be referred to in the method embodiment section, and details thereof are not repeated herein.
Example III
A third embodiment of the present invention provides a non-transitory computer readable storage medium having at least one instruction or at least one program stored therein, the at least one instruction or the at least one program loaded and executed by a processor to implement the steps of:
S100, obtaining a user list corresponding to each target IP and an IP list corresponding to each target user.
S200, according to the user list corresponding to each target IP, acquiring a first association degree between any two target IPs, and further acquiring a first association degree set.
S300, obtaining a second association degree between any two target users according to the IP list and the first association degree set corresponding to each target user, and further obtaining the second association degree set.
S400, acquiring a corresponding associated user list of each target user according to the second associated degree set and a preset associated degree threshold.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above functional units and the division of the modules are illustrated, and in practical application, the above functions may be allocated to different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the functions described above.
Example IV
A fourth embodiment of the present invention provides an electronic device including a processor and a non-transitory computer-readable storage medium in the third embodiment of the present invention.
The present invention is not limited to the above-mentioned embodiments, but is not limited to the above-mentioned embodiments, and any person skilled in the art can make some changes or modifications to the equivalent embodiments without departing from the scope of the present invention, but all the simple modifications, equivalent changes and modifications according to the technical matter of the present invention fall within the scope of the technical solution of the present invention.
Claims (7)
1. The data processing method for user line expansion is characterized in that the user line expansion is an associated user list corresponding to a target user, and the method comprises the following steps:
acquiring a user list corresponding to each target IP and an IP list corresponding to each target user, wherein the user list comprises IDs of a plurality of target users, and the IP list comprises a plurality of target IPs;
According to the user list corresponding to each target IP, a first association degree between any two target IPs is obtained, and then a first association degree set is obtained, wherein the step of obtaining the first association degree between any two target IPs according to the user list corresponding to each target IP further comprises the following steps:
Acquiring a user intersection and a user union between any two target IPs according to a user list corresponding to each target IP;
acquiring a first user quantity according to the user intersection;
acquiring a second user quantity according to the user union;
determining the ratio of the first user number to the second user number as a first association degree between any two target IPs;
According to the IP list corresponding to each target user and the first association degree set, obtaining a second association degree between any two target users, and further obtaining a second association degree set, wherein the step of obtaining the second association degree between any two target users according to the IP list corresponding to each target user and the first association degree set further comprises the following steps:
Acquiring an IP intersection and an IP union between any two target users according to the IP list corresponding to each target user;
acquiring a first weight corresponding to each target IP in the IP intersection according to the first association degree set;
acquiring the number of the IPs according to the IP union;
calculating the sum of first weights corresponding to all target IPs in the IP intersection, and determining the ratio of the sum of the first weights to the number of the IPs as a second association degree between any two target users;
The step of acquiring the first weight corresponding to each target IP in the IP intersection according to the first association degree set further includes the following steps:
taking any target IP in the IP intersection as an IP to be processed, and taking other target IPs except the IP to be processed in the IP intersection as candidate IPs;
according to the first association degree set, a first association degree between the IP to be processed and any candidate IP is obtained, and the average value of the first association degrees between the IP to be processed and all candidate IPs is calculated;
Determining the average value of the first association degree as a first weight corresponding to the IP to be processed;
Traversing each target IP in the IP intersection to obtain a first weight corresponding to each target IP in the IP intersection;
And acquiring a corresponding associated user list of each target user according to the second association degree set and a preset association degree threshold value.
2. The data processing method for user line expansion according to claim 1, further comprising the steps of:
Updating the first association degree according to the user list corresponding to each target IP and the second association degree set, acquiring a third association degree between any two target IPs, and further acquiring a third association degree set;
Updating the second association degree according to the IP list corresponding to each target user and the third association degree set, acquiring a fourth association degree between any two target users, and further acquiring a fourth association degree set;
and acquiring an updated associated user list corresponding to each target user according to the fourth associated degree set and the preset associated degree threshold.
3. The data processing method for user extension according to claim 2, wherein the step of updating the first association degree according to the user list corresponding to each target IP and the second association degree set to obtain a third association degree between any two target IPs further comprises the steps of:
Acquiring a second weight corresponding to each target user in the user interaction set according to the second association degree set;
And calculating second weight sum corresponding to all target users in the user intersection, and determining the ratio of the second weight sum to the second user quantity as a third association degree between any two target users.
4. The data processing method for user extension according to claim 3, wherein the step of updating the second association degree according to the IP list corresponding to each target user and the third association degree set to obtain a fourth association degree between any two target users further comprises the steps of:
Acquiring a third weight corresponding to each target IP in the IP intersection according to the third association degree set;
And calculating the third weight sum corresponding to all the target IPs in the IP intersection, and determining the ratio of the third weight sum to the IP number as a fourth association degree between any two target users.
5. A data processing apparatus for user expansion, wherein the user expansion is a list of associated users corresponding to a target user, the apparatus comprising:
The data acquisition module is used for acquiring a user list corresponding to each target IP and an IP list corresponding to each target user, wherein the user list comprises IDs of a plurality of target users, and the IP list comprises a plurality of target IPs;
the first association degree acquisition module is used for acquiring a first association degree between any two target IPs according to the user list corresponding to each target IP, and further acquiring a first association degree set, wherein the first association degree acquisition module further comprises the following sub-modules:
The first intersection acquisition sub-module is used for acquiring a user intersection and a user union between any two target IPs according to the user list corresponding to each target IP;
The first user quantity acquisition sub-module is used for acquiring the first user quantity according to the user intersection;
the second user quantity obtaining sub-module is used for obtaining the second user quantity according to the user union;
a first association degree obtaining sub-module, configured to determine a ratio of the first number of users to the second number of users as a first association degree between the arbitrary two target IPs;
The second association degree acquiring module is configured to acquire a second association degree between any two target users according to the IP list corresponding to each target user and the first association degree set, and further acquire the second association degree set, where the second association degree acquiring module further includes the following sub-modules:
The second intersection acquisition sub-module is used for acquiring an IP intersection and an IP union between any two target users according to the IP list corresponding to each target user;
The first weight acquisition sub-module is used for acquiring a first weight corresponding to each target IP in the IP intersection according to the first association degree set;
The IP quantity obtaining sub-module is used for obtaining the IP quantity according to the IP union;
A second association degree obtaining sub-module, configured to calculate a sum of first weights corresponding to all target IPs in the IP intersection, and determine a ratio of the sum of the first weights to the number of IPs as a second association degree between the arbitrary two target users;
the first weight obtaining sub-module further comprises the following units:
An IP classification unit, configured to take any target IP in the IP intersection as an IP to be processed, and take other target IPs in the IP intersection except the IP to be processed as candidate IPs;
the first average value calculation unit is used for acquiring a first association degree between the IP to be processed and any candidate IP according to the first association degree set, and calculating an average value of the first association degrees between the IP to be processed and all candidate IPs;
the first weight determining unit is used for determining the average value of the first association degree as a first weight corresponding to the IP to be processed;
The IP traversing unit is used for traversing each target IP in the IP intersection to acquire a first weight corresponding to each target IP in the IP intersection;
and the associated user acquisition module is used for acquiring an associated user list corresponding to each target user according to the second associated degree set and a preset associated degree threshold value.
6. A non-transitory computer readable storage medium having at least one instruction or at least one program stored therein, wherein the at least one instruction or the at least one program is loaded and executed by a processor to implement a data processing method for user expansion according to any of claims 1-4.
7. An electronic device comprising a processor and the non-transitory computer-readable storage medium of claim 6.
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